Artificial Neural Network Model to Predict Academic Results in Mathematics II

Guardado en:

书目详细资料
Autores:	Incio-Flores, Fernando Alain, Capuñay-Sanchez, Dulce Lucero, Estela-Urbina, Ronald Omar
格式:	artículo
状态:	Versión publicada
Fecha de Publicación:	2023
实物特征:	Objective. This article shows the design and training of an artificial neural network (ANN) to predict academic results of Civil Engineering students of the Fabiola Salazar Leguía National Intercultural University, from Bagua-Peru, in the subject of Mathematics II. Method. The CRISP-DM methodology was used, surveys were conducted to collect the data, and the RNA model was implemented in the Matlab software using the nnstart command and two learning algorithms: Scaled Conjugate Gradient (SCG) and Levenberg-Marquardt (LM). The performance of the model was evaluated through the mean square error and the correlation coefficient. Conclusions. The LM algorithm achieved better prediction effectiveness.
País:	Portal de Revistas UNA
机构:	Universidad Nacional de Costa Rica
Repositorio:	Portal de Revistas UNA
语言:	Español Inglés Portugués
OAI Identifier:	oai:ojs.www.una.ac.cr:article/14516
在线阅读:	https://www.revistas.una.ac.cr/index.php/EDUCARE/article/view/14516
Palabra clave:	Red neuronal artificial rendimiento académico predicción